Introduction In this project, you’ll get to build a neural network from scratch to carry out a prediction problem on a real dataset! By building a neural network from the ground up, you’ll have a much better understanding of gradient descent, backpropagation, and other concepts that are important to know Read more…
Training Optimization So by now we’ve learned how to build a deep neural network and how to train it to fit our data. Sometimes however, we go out there and train on ourselves and find out that nothing works as planned. Why? Because there are many things that can fail. Read more…
Gradient Descent with Squared Errors We want to find the weights for our neural networks. Let’s start by thinking about the goal. The network needs to make predictions as close as possible to the real values. To measure this, we use a metric of how wrong the predictions are, the error. Read more…
Introduction So let’s start with two questions, what is deep learning, and what is it used for? The answer to the second question is pretty much everywhere. Recent applications include things such as beating humans in games such as Go, or even jeopardy, detecting spam in emails, forecasting stock prices, Read more…
What is a neural network? The term, Deep Learning, refers to training Neural Networks, sometimes very large Neural Networks. So what exactly is a Neural Network? In this video, let’s try to give you some of the basic intuitions. Let’s start to the Housing Price Prediction example. Let’s say you have a data sets Read more…